Stochastic volatility models and the Taylor effect

It has been often empirically observed that the sample autocorrelations of absolute financial returns are larger than those of squared returns. This property, know as Taylor effect, is analysed in this paper in the Stochastic Volatility (SV) model framework. We show that the stationary autoregressive SV model is able to generate this property for realistic parameter specifications. On the other hand, the Taylor effect is shown not to be a sampling phenomena due to estimation biases of the sample autocorrelations. Therefore, financial models that aims to explain the behaviour of financial returns should take account of this property

El juego de dados de Mozart como recurso didáctico para dinamizar los procesos de enseñanza-aprendizaje de las nociones básicas de la probabilidad

Una de las tareas más importantes del docente es la transposición didáctica, que consiste en transformar el saber abstracto en un saber enseñado, que se acomode a las necesidades de los estudiantes y que cumpla la función de ser significativo. En ese orden de ideas, el uso de recursos didácticos y la gestión docente facilitan tal tarea. En efecto, este taller consiste en la aplicación del recurso “Juego de dados de Mozart”, y tiene como finalidad ilustrar en qué consiste el juego, con ayuda de medios tecnológicos que permiten que cada persona pueda crear diversas composiciones musicales por medio del azar, y que, además, construya algunos conceptos de probabilidad. De esta manera se hará un aporte a la didáctica de la estocástica y, por ende, una propuesta para enseñar probabilidad por medio de un recurso innovador y que se puede adaptar para abordar diferentes conceptos

The role of carbon nanotubes on the stability of tetragonal zirconia polycrystals

The effect of single walled carbon nanotubes (SWNT) at zirconia grain boundaries on the stability of a tetragonal zirconia polycrystalline matrix has been explored in as–sintered composites and after low–temperature hydrothermal degradation (LTD) experiments. For this purpose, highly–dense 3 mol% Y2O3–doped tetragonal zirconia polycrystalline (3YTZP) ceramics and SWNT/3YTZP composites were prepared by spark plasma sintering (SPS). Quantitative X–ray diffraction analysis and microstructural observations point out that an increasing amount of well–dispersed SWNT bundles surrounding zirconia grains decreases the metastable tetragonal phase retention in the ceramic matrix after sintering. In contrast, the tetragonal ceramic grains in composites with SWNTs are less sensitive to the presence of water, i.e. to undergo a martensitic transformation under LTD conditions, than monolithic 3YTZP ceramics. The SWNT incorporation diminishes micro–cracking due to tetragonal to monoclinic ZrO2 phase transformation in the composites.Ministerio de Economía y Competitividad de España y Fondos Europeos FEDER - MAT2015–67889–PJunta de Andalucía - P12–FQM–107

A scalable evolvable hardware processing array

Evolvable hardware (EH) is an interesting alternative to conventional digital circuit design, since autonomous generation of solutions for a given task permits self-adaptivity of the system to changing environments, and they present inherent fault tolerance when evolution is intrinsically performed. Systems based on FPGAs that use Dynamic and Partial Reconfiguration (DPR) for evolving the circuit are an example. Also, thanks to DPR, these systems can be provided with scalability, a feature that allows a system to change the number of allocated resources at run-time in order to vary some feature, such as performance. The combination of both aspects leads to scalable evolvable hardware (SEH), which changes in size as an extra degree of freedom when trying to achieve the optimal solution by means of evolution. The main contributions of this paper are an architecture of a scalable and evolvable hardware processing array system, some preliminary evolution strategies which take scalability into consideration, and to show in the experimental results the benefits of combined evolution and scalability. A digital image filtering application is used as use case

Noise-agnostic adaptive image filtering without training references on an evolvable hardware platform

One of the main concerns of evolvable and adaptive systems is the need of a training mechanism, which is normally done by using a training reference and a test input. The fitness function to be optimized during the evolution (training) phase is obtained by comparing the output of the candidate systems against the reference. The adaptivity that this type of systems may provide by re-evolving during operation is especially important for applications with runtime variable conditions. However, fully automated self-adaptivity poses additional problems. For instance, in some cases, it is not possible to have such reference, because the changes in the environment conditions are unknown, so it becomes difficult to autonomously identify which problem requires to be solved, and hence, what conditions should be representative for an adequate re-evolution. In this paper, a solution to solve this dependency is presented and analyzed. The system consists of an image filter application mapped on an evolvable hardware platform, able to evolve using two consecutive frames from a camera as both test and reference images. The system is entirely mapped in an FPGA, and native dynamic and partial reconfiguration is used for evolution. It is also shown that using such images, both of them being noisy, as input and reference images in the evolution phase of the system is equivalent or even better than evolving the filter with offline images. The combination of both techniques results in the completely autonomous, noise type/level agnostic filtering system without reference image requirement described along the paper

Real-Time Wireless Platform for In Vivo Monitoring of Bone Regeneration

For the monitoring of bone regeneration processes, the instrumentation of the fixation is an increasingly common technique to indirectly measure the evolution of bone formation instead of ex vivo measurements or traditional in vivo techniques, such as X-ray or visual review. A versatile instrumented external fixator capable of adapting to multiple bone regeneration processes was designed, as well as a wireless acquisition system for the data collection. The design and implementation of the overall architecture of such a system is described in this work, including the hardware, firmware, and mechanical components. The measurements are conditioned and subsequently sent to a PC via wireless communication to be in vivo displayed and analyzed using a developed real-time monitoring application. Moreover, a model for the in vivo estimation of the bone callus stiffness from collected data was defined. This model was validated in vitro using elastic springs, reporting promising results with respect to previous equipment, with average errors and uncertainties below 6.7% and 14.04%. The devices were also validated in vivo performing a bone lengthening treatment on a sheep metatarsus. The resulting system allowed the in vivo mechanical characterization of the bone callus during experimentation, providing a low-cost, simple, and highly reliable solution.Junta de Andalucía US-1261691Ministerio de Economía y Competitividad DPI2017-82501-PMinisterio de Economía y Competitividad PGC2018-097257-B-C3

Effect of high SWNT content on the room temperature mechanical properties of fully dense 3YTZP/SWNT composites

This paper is devoted to correlate the microstructure and room temperature mechanical properties of single-wall carbon nanotube (SWNT) reinforced 3. mol% yttria stabilized tetragonal zirconia with high SWNT content (2.5, 5 and 10. vol%). Fully dense composites were prepared by using a combination of aqueous colloidal powder processing and Spark Plasma Sintering. SWNTs were located at the ceramic grain boundaries and they were not damaged during the sintering process. The weak interfacial bonding between SWNTs and ceramic grains together with the detachment of SWNTs within thick bundles have been pointed out as responsible for the decrease of hardness and fracture toughness of the composites in comparison with the monolithic 3YTZP ceramic.Ministerio de Ciencia e Innovación (España) MAT2012-34217Junta de Andalucía P12-FQM-107

Modelling long-memory volatilities with leverage effect: A-LMSV versus FIEGARCH

A new stochastic volatility model, called A-LMSV, is proposed to cope simultaneously with leverage effect and long-memory in volatility. Its statistical properties are derived and compared with the properties of the FIEGARCH model. It is shown that the dependence of the autocorrelations of squares on the parameters measuring the asymmetry and the persistence is different in both models. The kurtosis and autocorrelations of squares do not depend on the asymmetry in the A-LMSV model while they increase with the asymmetry in the FIEGARCH model. Furthermore, the autocorrelations of squares increase with the persistence in the A-LMSV model and decrease in the FIEGARCH model. On the other hand, if the correlation between returns and future volatilities is negative, the autocorrelations of absolute returns increase with the magnitude of the asymmetry in the FIEGARCH model while they decrease in the A-LMSV model. Finally, the cross-correlations between squares and original observations are, in general, larger in absolute value in the FIEGARCH model than in the A-LMSV model. The results are illustrated by fitting both models to represent the dynamic evolution of volatilities of daily returns of the S&P500 and DAX indexes.Publicad

A self-adaptive image processing application based on evolvable and scalable hardware

Evolvable Hardware (EH) is a technique that consists of using reconfigurable hardware devices whose configuration is controlled by an Evolutionary Algorithm (EA). Our system consists of a fully-FPGA implemented scalable EH platform, where the Reconfigurable processing Core (RC) can adaptively increase or decrease in size. Figure 1 shows the architecture of the proposed System-on-Programmable-Chip (SoPC), consisting of a MicroBlaze processor responsible of controlling the whole system operation, a Reconfiguration Engine (RE), and a Reconfigurable processing Core which is able to change its size in both height and width. This system is used to implement image filters, which are generated autonomously thanks to the evolutionary process. The system is complemented with a camera that enables the usage of the platform for real time applications

A novel FPGA-based evolvable hardware system based on multiple processing arrays

In this paper, an architecture based on a scalable and flexible set of Evolvable Processing arrays is presented. FPGA-native Dynamic Partial Reconfiguration (DPR) is used for evolution, which is done intrinsically, letting the system to adapt autonomously to variable run-time conditions, including the presence of transient and permanent faults. The architecture supports different modes of operation, namely: independent, parallel, cascaded or bypass mode. These modes of operation can be used during evolution time or during normal operation. The evolvability of the architecture is combined with fault-tolerance techniques, to enhance the platform with self-healing features, making it suitable for applications which require both high adaptability and reliability. Experimental results show that such a system may benefit from accelerated evolution times, increased performance and improved dependability, mainly by increasing fault tolerance for transient and permanent faults, as well as providing some fault identification possibilities. The evolvable HW array shown is tailored for window-based image processing applications